Why use the Agent SDKs and all these abstractions? If you want to take control of the foundation of LLM Agents, in this AI era, you can always start from scratch and build your own "high-scrapers".
Http
- use
tuner.as_oai_baseurl_apikey()to obtain baseurl + apikey arguments
Explain with examples
# tuner to api key
base_url = "https://openrouter.ai/api/v1"
api_key = "sk-1234567"
# take out query
query = workflow_task.task.main_query
messages = [
{
"role": "system",
"content": self.system_prompt
},
{
"role": "user",
"content": query
}
]
# use raw http requests (non-streaming) to get response
response = requests.post(
f"{base_url}/chat/completions",
json={
"model": "fill_whatever_model", # Of course, this `model` field will be ignored.
"messages": messages,
},
headers={
"Authorization": f"Bearer {api_key}"
}
)
final_answer = response.json()['choices'][0]['message']['content']
# tuner to api key
url_and_apikey = tuner.as_oai_baseurl_apikey()
base_url = url_and_apikey.base_url
api_key = url_and_apikey.api_key
# take out query
query = workflow_task.task.main_query
messages = [
{
"role": "system",
"content": self.system_prompt
},
{
"role": "user",
"content": query
}
]
# use raw http requests (non-streaming) to get response
response = requests.post(
f"{base_url}/chat/completions",
json={
"model": "fill_whatever_model", # Of course, this `model` field will be ignored.
"messages": messages,
},
headers={
"Authorization": f"Bearer {api_key}"
}
)
final_answer = response.json()['choices'][0]['message']['content']